Derek Tam
Impact in
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- Topic Modeling
- Natural Language Processing Techniques
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
Papers in
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- Natural Language Processing Techniques 3
- Topic Modeling 2
-
- Appendicitis Diagnosis and Management 2
- Hematological disorders and diagnostics 1
- Co-authors
- Colin Raffel (2 shared papers)Mohit Bansal (2 shared papers)Diyi Yang (1 shared paper)Jiaao Chen (1 shared paper)Shiyue Zhang (1 shared paper)Dian Yu (1 shared paper)Steven Franconeri (1 shared paper)Aly Karsan (2 shared papers)
- Journals
- Transactions of the Association for Computational Linguistics (1 paper)Cognition (1 paper)Blood (1 paper)The American Journal of Emergency Medicine (1 paper)Nature Communications (1 paper)
- Partner nations
- United StatesCanadaHong Kong
In The Last Decade
Derek Tam
12 papers receiving 139 citations
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 75
- Health Informatics 2
- General Social Sciences 4
- Hepatology 7
- Emergency Medicine 7
Countries citing papers authored by Derek Tam
This map shows the geographic impact of Derek Tam's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Derek Tam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Derek Tam more than expected).
Fields of papers citing papers by Derek Tam
This network shows the impact of papers produced by Derek Tam. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Derek Tam. The network helps show where Derek Tam may publish in the future.
Co-authors
The 25 scholars most cited alongside Derek Tam, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 75 | |
| 2 | 2023 | 23 | |
| 3 | 2023 | 11 | |
| 4 | 2018 | 10 | |
| 5 | 2022 | 7 | |
| 6 | 2022 | 7 | |
| 7 | 2017 | 6 | |
| 8 | Calculated decisions: Jones criteria for acute rheumatic fever diagnosis | 2020 | 2 |
| 9 | Calculated decisions: Pediatric appendicitis risk calculator (pARC) | 2019 | 1 |
| 10 | Calculated decisions: Pediatric NIHSS Stroke Scale (PedNIHSS). | 2023 | 1 |
| 11 | 2022 | 1 | |
| 12 | 2017 | 1 |
About Derek Tam
Derek Tam is a scholar working on Artificial Intelligence, Emergency Medicine, Computer Vision and Pattern Recognition, Cell Biology and Surgery, having authored 12 papers that have together received 145 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (3 papers), Topic Modeling (2 papers), Zebrafish Biomedical Research Applications (2 papers), Appendicitis Diagnosis and Management (2 papers), Multimodal Machine Learning Applications (1 paper), Hematological disorders and diagnostics (1 paper), Computational and Text Analysis Methods (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Artificial Intelligence (75 citations), Health Informatics (2 citations), General Social Sciences (4 citations), Hepatology (7 citations) and Emergency Medicine (7 citations). Derek Tam has collaborated with scholars based in United States, Canada and Hong Kong. Frequent co-authors include Colin Raffel, Mohit Bansal, Diyi Yang, Jiaao Chen, Shiyue Zhang, Dian Yu, Steven Franconeri, Aly Karsan, Misha Bilenky and Grace Cole. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Cognition, Blood, The American Journal of Emergency Medicine and Nature Communications.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.